Simplifying Enterprise Data Integration: A Deep Dive into Snowflake Openflow’s BYOC Deployment

To derive valuable data-driven insights — whether through analytics, machine learning or search — businesses are constantly looking for better ways to manage the mountains of information they possess. Historically, though, that’s been much easier said than done. In practice, it requires building (and maintaining) complex integration pipelines that quickly become cumbersome, not to mention costly. 

For many, a data integration service that is adaptable and extendable, yet easy to manage and control, may sound like a pipe(line) dream, and yet that’s precisely what Snowflake Openflow was designed to provide. Openflow offers two deployment options: Snowflake-hosted and customer-hosted. The customer-hosted option, based on a bring your own cloud (BYOC) deployment, is generally available in all AWS commercial regions. With these deployment options, Openflow offers the flexibility to run data flows wherever customer data resides without impacting existing privacy or security — all while maintaining operational simplicity.

In this blog post, the first in a two-part series, we are going to dive deeper into BYOC — what it is, why it can be beneficial for your team and when to use BYOC. Later, we will walk through both customer-hosted and Snowflake-hosted options. 

The beauty of BYOC

When it comes to data movement and networking, companies typically have to choose between two types of deployments — a fully managed SaaS option or a self-hosted alternative — each with its benefits and trade-offs. A managed SaaS offering is easy to set up and maintain but often lacks flexibility, while self-hosting allows for greater control and customization but requires much more work, particularly at the outset. 

The BYOC option, however, has emerged as a middle ground — a Goldilocks solution that offers the benefits of each: convenient and scalable, with flexibility and control. With BYOC, companies enjoy the experience of a managed service right on top of their cloud infrastructure. They’re able to connect public and private systems securely and handle sensitive data preprocessing locally, within the secure bounds of the organization’s cloud environment. For larger enterprises, BYOC also offers the opportunity to take advantage of any preferred pricing they may receive from their existing cloud infrastructure contracts, which helps the bottom line. For all of these reasons and more, the BYOC model has been gaining popularity of late.

Data flows with flexibility

Snowflake’s BYOC deployment of Openflow is designed to meet customers where their data lives. It unlocks sophisticated data engineering capabilities while preserving data sovereignty and maintaining continuity across many systems. With BYOC, Snowflake takes on the heavy lifting of managing the Openflow deployment and runtimes that are hosted on customer infrastructure. We simplify aspects like observability and orchestration of pipelines with a single pane of glass, marrying ease of use with flexibility.

With a BYOC deployment, Snowflake helps manage:

• Installation complexity: Understanding the details of a given cloud environment, then generating infrastructure-as-code assets that can be easily shared with a cloud platform team, which greatly simplifies deployment. 

• Integrated observability: Gain deep visibility into your integration pipelines with a detailed DAG view and data lineage. 

• Security: Providing advanced security features, including authentication, fine-grained authorization, encryption in transit, secrets management, AWS PrivateLink and tri-secret secure. 

But the greatest benefit of an Openflow BYOC deployment is the flexibility that Snowflake provides. It allows companies to deploy pipelines securely in whatever way works best with their existing architecture and network design. It supports data movement from any source to any destination with the freedom to use new or established infrastructure, depending on the company’s needs. Instead of forcing data to flow down rigid, prescribed pathways — or needing to engineer complex and expensive workarounds at every turn — Openflow is built to forge pipelines that are both powerful and flexible. 

For a full explanation of what a BYOC deployment requires — from the security model and required permissions, to the flexible networking options provided in the guided deployment wizard and more — please refer to the Openflow documentation.

Openflow everywhere

At Snowflake, we believe that companies will need to run data flows close to their critical data systems, wherever they may live. Whether Openflow runs fully managed within Snowflake (through Snowpark Container Services*) or helps companies write to externally managed Apache Iceberg™ tables, it puts the power of choice in the user’s hands. 

Deploying flexible compute, Openflow allows data engineers to provision runtimes (compute clusters similar in spirit to warehouses) in a self-service way. These runtimes come built in with both the UI for flow authorship as well as the compute needed for flow execution. So no matter the data type — structured or unstructured, batch or streaming — Openflow provides organizations with everything they need to modernize their data ingestion architecture. It holds the keys to enterprise AI, enabling seamless ETL and revolutionizing data movement altogether — in Snowflake and beyond.

To get started with a BYOC deployment of Openflow, check out the getting started guide. 

Also, join us on July 29 for Data Engineering Connect: Streamline Data Pipeline Workflows with ZeroOps to learn how Snowflake empowers data engineers to automate pipelines with confidence — freeing them from operational overhead and letting them focus on what matters most.

*Currently in private preview for AWS and Azure